Hepatic Gene Expression Analysis

22160 R for bio data science

Antoine Andréoletti, Olivier Gaufrès, Amy Surry, Lea Skytthe, and Trine Søgaard

Introduction

Aim

Investigating hepatic gene expression by comparing expression levels across:

  • Healthy individuals
  • Patients with NAFLD
  • Patients with cirrhosis

Data

  • RNA-seq: from patients with NAFLD, patients with cirrhosis, and healthy controls under both fasting and postprandial conditions
  • Meta data: additional information about patients

Data processing

Data processing

Methods



Descriptive analysis


  • Distributions are fairly equal throughout our data
  • Sick people are older on average
  • No significance in disease between men and women

PCA & Heatmap

Differential Expression Analysis

Compare gene expression levels between groups using DESeq2

Output for each gene: Global Mean - Fold-change - Adjusted p-value

Gene Set Enrichment Analysis

Investigating hepatic gene set enrichment


  • C11 hepatocytes is a subtype of hepatocytes (1 of 3)
  • Hepatocytes produces hepatokines (hormone involved in metabolic regulation)
  • Some therapies try to promote hepatocyte regeneration

Discussion / Conclusion

  • Key findings:
    • No clear distinction of patients in relation to gene expression.
    • Difference for fasting patients - healthy vs sick
      • NAFLD patients have altered gene expression compared to normal patients
      • Hepatic gene set enrichment change
  • A bit of troubles with DESeq2 package for tidy workflow
  • Project workflow designed to facilitate easy continuation and further analysis

Group 20